Effects of Climate, Plant Height, and Evolutionary Age on Geographical Patterns of Fruit Type.

Fruit type is a key reproductive trait associated with plant evolution and adaptation. However, large-scale geographical patterns in fruit type composition and the mechanisms driving these patterns remain to be established. Contemporary environment, plant functional traits and evolutionary age may all influence fruit type composition, while their relative importance remains unclear. Here, using data on fruit types, plant height and distributions of 28,222 (∼ 90.1%) angiosperm species in China, we analyzed the geographical patterns in the proportion of fleshy-fruited species for all angiosperms, trees, shrubs, and herbaceous species separately, and compared the relative effects of contemporary climate, ecosystem primary productivity, plant height, and evolutionary age on these patterns. We found that the proportion of fleshy-fruited species per grid cell for all species and different growth forms all showed significant latitudinal patterns, being the highest in southeastern China. Mean plant height per grid cell and actual evapotranspiration (AET) representing ecosystem primary productivity were the strongest drivers of geographical variations in the proportion of fleshy-fruited species, but their relative importance varied between growth forms. From herbaceous species to shrubs and trees, the relative effects of mean plant height decreased. Mean genus age had significant yet consistently weaker effects on proportion of fleshy-fruited species than mean plant height and AET, and environmental temperature and precipitation contributed to those of only trees and shrubs. These results suggest that biotic and environmental factors and evolutionary age of floras jointly shape the pattern in proportion of fleshy-fruited species, and improve our understanding of the mechanisms underlying geographical variations in fruit type composition. Our study also demonstrates the need of integrating multiple biotic and abiotic factors to fully understand the drivers of large-scale patterns of plant reproductive traits.